Barfinex
Bullish

Rising new address creation and sustained active address growth for ONG

TechnicalDirection:BullishSeverity:Medium

Pattern:

ONG functions as the gas token for Ontology-based operations; therefore, increases in on-chain user activity and new address creation are repeatable leading indicators for increased utility demand.

Monitoring methodology:

  • track daily new address counts, 7-day and 30-day moving averages, and active addresses (addresses with txs per day);
  • compute retention/cohort metrics to distinguish transient spikes (airdrops, bot activity) from sustained user growth;
  • monitor transaction counts per address, smart-contract interaction rates, and average gas consumed per transaction to estimate marginal ONG demand;
  • cross-reference with off-chain signals such as dApp TVL changes, developer commits, and partnership announcements to add conviction.

Typical trigger:

Sustained increase in new addresses and active addresses with cohort retention > X% over 14–30 days and rising average gas per tx.

Market mechanics:

Rising genuine user activity increases real demand for ONG to pay for gas and interact with contracts, reducing available sell pressure and supporting higher price levels.

Distinguishing noise:

Short bursts of address growth from marketing campaigns or ephemeral airdrops often show low retention and low per-address activity — filter these with cohort analysis and on-chain heuristics (e.g., small value transfers, identical behavior patterns).

Risk considerations:

Growth in addresses does not guarantee price appreciation if supply-side policies or large sell-side holders offset demand; combine with exchange balance and liquidity metrics for a holistic view.

Actionable use:

Set alerts for multiple on-chain indicators moving in tandem (new addresses, active addresses, gas per tx), and use them to time entries or scale into positions as utility demand becomes observable.

This technical/on-chain pattern is repeatable for ONG because its value proposition is directly tied to network usage, making these metrics directly applicable for monitoring.

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